Computer vision has a wide range of uses in photography, document processing, manufacturing, and other areas. A common function of computer vision systems is to identify or recognize objects that appear in an image. In photographic processing, for example, computer vision systems may identify people, faces, etc. In manufacturing, computer vision systems may identify manufactured articles, often including defects in the articles. In document processing, computer vision systems may identify letters or words in a process often referred to as optical character recognition (OCR).
Many common computer vision systems identify objects in a test image by applying classifiers. Classifiers describe image properties known to correspond to a particular object type (e.g., a car, a face, a particular letter or other character, etc.). If properties of the test image correlate to the classifier, then the computer vision system concludes that the test image shows an example of the object type. For example, if the properties of an image correlate to a classifier for a car, then the computer vision system may conclude that the test image shows a car. The performance of object classifiers, however, can be compromised if the appearance of an object in a test image is translated or distorted.